Language as a matrix product state

Pestun, Vasily, Terilla, John, Vlassopoulos, Yiannis

arXiv.org Machine Learning 

We propose a statistical model for natural language that begins by considering language as a monoid, then representing it in complex matrices with a compatible translation invariant probability measure. We interpret the probability measure as arising via the Born rule from a translation invariant matrix product state.

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